aurum-recall
A memory system for AI agents that maintains a human-readable, typed Markdown knowledge base with an always-in-context index, enabling recall, correction, and trust decay through MCP.
README
Aurum Recall
AI-native memory you and your agent can actually read — and navigate.
Two layers, one system:
- The Store — sovereign, human-readable, self-curating memory: typed Markdown files + an
always-in-context index +
[[links]]+ trust-decay. A library and an MCP server. - The Lattice (ContextQR) — a visual routing layer over that store: color-coded context tiles, trust borders, and a real scannable root QR. Route before you retrieve.
<p align="center"> <img src="assets/example_map.svg" alt="Aurum Recall lattice — color-coded context routers" width="560"> <img src="assets/example_qr.png" alt="Scannable root QR" width="170"> </p>
The store is where memory lives. The lattice is how an agent flies through it — narrowing to the right branch, respecting privacy and freshness, and pulling only what it needs, before spending tokens on retrieval.
Why
Vector-DB memory is opaque, unownable, and un-auditable — and RAG retrieves text first, with no cheap way to route. Aurum Recall inverts both:
Vector RAG: Question → embedding search → maybe-relevant chunks → answer
Aurum Recall: Question → route the lattice → narrow the branch → search inside it → verify → answer
You get lower token use, real privacy boundaries, first-class trust/freshness/provenance, and a memory that is your files, in the open, on your terms.
Context windows do not expire. They crystallize into recursive memory tiles. When an agent's
context fills, it compresses into a tile; 64 tiles seal into an 8×8 layer; layers hash-chain
(Merkle) and recurse. The architecture: CONCEPT.md.
The Store
- One durable fact per file, typed (
user/feedback/project/reference), with a one-line hook.MEMORY.mdis the always-loaded index — the working set. Full format:SPEC.md. - Zero-dependency core:
recall / remember / update / forget / link / compact. Trust decays with age. - MCP server — one config line and any MCP agent (Claude Desktop, Claude Code) gets durable,
inspectable memory. See
QUICKSTART.md.
npm install && npm run build && npm test
The Lattice (ContextQR)
Build a routable visual lattice from a real memory store, render it, and mint the root QR:
node dist/lattice/cli.js from-store <memory-dir> --out lattice.json
node dist/lattice/cli.js validate lattice.json
node dist/lattice/cli.js render lattice.json --out map.svg
node dist/lattice/cli.js qr lattice.json --out root_qr.png
node dist/lattice/cli.js subtree lattice.json ctx_type_project --out projects.svg
node dist/lattice/cli.js inspect lattice.json ctx_type_project
Color = context type · border = trust level · brightness = freshness · marker = machine-readable pointer. Only the root is a literal scannable QR; deeper tiles are recursive routers, not nested pixels.
The moat isn't QR codes — it's the combination: visual context routing + context crystallization + recursive 8×8 layers + trust/freshness/privacy metadata + hash-verifiable provenance + agent navigation before retrieval.
Open core
Public (the credibility layer, this repo): the memory store + MCP server + lens, and the lattice — schema, validator, SVG renderer, root QR, CLI, the store→lattice importer, and the concept paper.
Private (the commercial layer, not built in public): the production routing engine, memory & compression heuristics, trust/freshness/privacy scoring logic, persistence, cloud service, and product integrations (Nomad, the AgentX-Ray "Context Navigation" benchmark).
Apache-2.0 · Aurum Nebula LLC · SPEC.md · CONCEPT.md · BUILD_PLAN.md
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。